MetaculR_probabilistic_consensus {MetaculR} | R Documentation |
Generate probabilistic consensus from multiple parameterized forecasts
Description
Generate probabilistic consensus from multiple parameterized forecasts
Usage
MetaculR_probabilistic_consensus(f)
Arguments
f |
A list of forecasts (see example for necessary structure). |
Value
A list of forecasts.
pdf |
A dataframe of probability density functions corresponding to original forecasts and consensus forecast. |
cdf |
A dataframe of cumulative distribution functions corresponding to original forecasts and consensus forecast. |
summary |
A dataframe of summary statistics corresponding to original forecasts and consensus forecast, i.e., 10th, 25th, 50th, 75th, 90th centiles and mean. |
References
McAndrew, T., & Reich, N. G. (2020). An expert judgment model to predict early stages of the COVID-19 outbreak in the United States [Preprint]. Infectious Diseases (except HIV/AIDS). https://doi.org/10.1101/2020.09.21.20196725
Examples
## Not run:
forecasts <- list(list(range = c(0, 250), resolution = 1),
list(source = "Pishkalo",
dist = "Norm",
params = c("mu", "sd"),
values = c(116, 12),
weight = 0.2),
list(source = "Miao",
dist = "Norm",
params = c("mu", "sd"),
values = c(121.5, 32.9)),
list(source = "Labonville",
dist = "TPD",
params = c("min", "mode", "max"),
values = c(89-14, 89, 89+29)),
list(source = "NOAA",
dist = "PCT",
params = c(0.2, 0.8),
values = c(95, 130)),
list(source = "Han",
dist = "Norm",
params = c("mu", "sd"),
values = c(228, 40.5)),
list(source = "Dani",
dist = "Norm",
params = c("mu", "sd"),
values = c(159, 22.3)),
list(source = "Li",
dist = "Norm",
params = c("mu", "sd"),
values = c(168, 6.3)),
list(source = "Singh",
dist = "Norm",
params = c("mu", "sd"),
values = c(89, 9)))
MetaculR_probabilistic_consensus(
f = forecasts)
## End(Not run)
[Package MetaculR version 0.4.1 Index]